SEAug 25, 2014

Staged Evolution with Quality Gates for Model Libraries

arXiv:1408.5707v15 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of managing model evolution and quality in model libraries for researchers and practitioners, but it appears incremental as it builds on existing concepts like evolution graphs.

The paper tackles the lack of structured approaches for model evolution in model libraries by proposing a quality staged evolution theory based on evolution graphs and quality gates, resulting in a framework that partitions evolution steps into stages to manage quality concerns.

Model evolution is widely considered as a subject under research. Despite its role in research, common purpose concepts, approaches, solutions, and methodologies are missing. Limiting the scope to model libraries makes model evolution and related quality concerns manageable, as we show below. In this paper, we put forward our quality staged model evolution theory for model libraries. It is founded on evolution graphs, which offer a structure for model evolution in model libraries through evolution steps. These evolution steps eventually form a sequence, which can be partitioned into stages by quality gates. Each quality gate is defined by a lightweight quality model and respective characteristics fostering reusability.

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